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Artificial Intelligence in Surgical Coding: Evaluating Large Language Models for Current Procedural Terminology

Emily L Isch1, Jamie Lee2, D Mitchell Self3

  • 1Department of General Surgery, Thomas Jefferson University, Philadelphia, PA.

Journal of Hand Surgery Global Online
|April 4, 2025
PubMed
Summary
This summary is machine-generated.

Large language models show promise for surgical Current Procedural Terminology (CPT) coding. Perplexity.AI and Bard performed best in identifying CPT codes for hand surgery procedures, indicating AI

Keywords:
AI in surgeryCPT codingChatGPTCurrent Procedural TerminologyHand surgery efficiencyLarge language models

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Surgical Informatics
  • Medical Coding Automation

Background:

  • Large language models (LLMs) are advancing surgical disciplines.
  • Current Procedural Terminology (CPT) coding is complex and time-consuming.
  • There's a need for efficient and accurate CPT coding solutions due to coder scarcity.

Purpose of the Study:

  • To evaluate the effectiveness of five LLMs in accurately identifying CPT codes for hand surgery.
  • To compare the performance of Perplexity.AI, Bard, BingAI, ChatGPT 3.5, and ChatGPT 4.0 in CPT coding.

Main Methods:

  • An observational study tested five publicly available LLMs.
  • A consistent query format was used to assess CPT code identification for hand surgery procedures.
  • Responses were classified as correct, partially correct, or incorrect.

Main Results:

  • Perplexity.AI (15) and Bard/BingAI (14) showed the highest accuracy for simple procedures.
  • ChatGPT models had lower accuracy for simple procedures (7-8 correct).
  • For complex procedures, Perplexity.AI and Bard achieved three correct outcomes; ChatGPT models had none. Bing AI led in partially correct outcomes (5).

Conclusions:

  • LLMs demonstrate feasibility for CPT coding in hand surgery.
  • Further AI model refinement is needed to enhance accuracy and practicality.
  • AI-assisted coding may become a standard in surgical workflows, supporting healthcare's digital transformation.